Cette thèse étudie le problème d'identification de la topologie d'un réseau de systèmes complexes dynamiques, dont les sous-systèmes sont décrits par des équations différentielles ordinaires (EDO) et/ou par des équations différentielles à retard (EDR). La première partie de ce travail porte sur l’identification des paramètres du réseau de systèmes linéaires. Ainsi, différentes classes de systèmes linéaires ont été traitées, à savoir les systèmes sans retard, les systèmes à retard commensurable et les systèmes à entrées inconnues. Un observateur impulsif est proposé afin d'identifier à la fois les états et les paramètres inconnus de la classe de système dynamique considérée en temps fini. Afin de garantir l'existence de l'observateur impulsif proposé, des conditions suffisantes sont déduites. Des exemples illustratifs sont donnés afin de montrer l'efficacité de l'observateur en temps fini proposé.La deuxième partie de ce travail traite le problème de l'identification de la topologie d'un réseau de systèmes dynamiques non linéaires. Dans nos considérations, les coefficients interconnexions de la topologie du réseau sont considérés comme des paramètres constants. Par conséquent, l'identification de la topologie est équivalente à l'identification des paramètres inconnus. Tout d’abord, nous avons déduit des conditions suffisantes sur l’identifiabilité des paramètres, puis nous avons proposé un différenciateur uniforme avec convergence en temps fini pour estimer les paramètres inconnus / This thesis investigates the topology identification problem for network of dynamical complex systems, whose subsystems are described by ordinary differential equations (ODE) and/or delay differential equations (DDE). The first part of this work focuses on the parameters identification of the network of linear systems. Thus, different classes of linear systems have been treated namely systems without delay, systems with commensurable delay and systems with unknown inputs. An impulsive observer is proposed in order to identify both the states and the unknown parameters of the considered class of dynamic system in finite time. In order to guarantee the existence of the proposed impulsive observer, sufficient conditions are deduced. An illustrative example is given in order to show the efficiency of the proposed finite-time observer.The second part of this work treats the topology identification of the network of nonlinear dynamic systems. In our considerations, the topology connections are represented as constant parameters, therefore the topology identification is equivalent to identify the unknown parameters. A sufficient condition on parameter identifiability is firstly deduced, and then a uniform differentiator with finite-time convergence is proposed to estimate the unknown parameters

Nonlinear systems occur in industrial processes, economical systems, biotechnology and in many other areas. The thesis treats methods for system identification and control of such nonlinear systems, and applies the proposed methods to a solar heating/cooling plant. Two applications, an anaerobic digestion process and a domestic solar heating system are first used to illustrate properties of an existing nonlinear recursive prediction error identification algorithm. In both cases, the accuracy of the obtained nonlinear black-box models are comparable to the results of application specific grey-box models. Next a convergence analysis is performed, where conditions for convergence are formulated. The results, together with the examples, indicate the need of a method for providing initial parameters for the nonlinear prediction error algorithm. Such a method is then suggested and shown to increase the usefulness of the prediction error algorithm, significantly decreasing the risk for convergence to suboptimal minimum points. Next, the thesis treats model based control of systems with input signal dependent time delays. The approach taken is to develop a controller for systems with constant time delays, and embed it by input signal dependent resampling; the resampling acting as an interface between the system and the controller. Finally a solar collector field for combined cooling and heating of office buildings is used to illustrate the system identification and control strategies discussed earlier in the thesis, the control objective being to control the solar collector output temperature. The system has nonlinear dynamic behavior and large flow dependent time delays. The simulated evaluation using measured disturbances confirm that the controller works as intended. A significant reduction of the impact of variations in solar radiation on the collector outlet temperature is achieved, though the limited control range of the system itself prevents full exploitation of the proposed feedforward control. The methods and results contribute to a better utilization of solar power.

The main interest of the present thesis is the constrained control of time-delay system, more specifically taking into consideration the discretization problem (due to, for example, a communication network) and the presence of constraints in the system's trajectories and control inputs. The effects of data-sampling and modeling problem are studied in detail, where an uncertainty is added into the system due to additional effect of the discretization and delay. The delay variation with respect to the sampling instants is characterized by a polytopic supra-approximation of the discretization/delay induced uncertainty. Some stabilizing techniques, based on Lyapunov's theory, are then derived for the unconstrained case. Lyapunov-Krasovskii candidates were also used to obtain LMI conditions for a state feedback, in the ''original" state-space of the system. For the constrained control purposes, the set invariance theory is used intensively, in order to obtain a region where the system is ''well-behaviored", despite the presence of constraints and (time-varying) delay. Due to the high complexity of the maximal delayed state admissible set obtained in the augmented state-space approach, in the present manuscript we proposed the concept of set invariance in the ''original" state-space of the system, called D-invariance. Finally, in the las part of the thesis, the MPC scheme is presented, in order to take into account the constraints and the optimality of the control solution.

Chaotic dynamics produced by optical delay systems have interesting applications in telecommunications. Optical chaos can be used to transmit secretly, in real-time, a message between an emitter and a receiver. The noise-like appearance of chaos is used to conceal the message, and the synchronization of the receiver with the chaotic emitter is used to decode the message. This work focuses on the study of two crucial topics in the field of chaotic optical communications. The first topic is the synchronization of chaotic external-cavity laser diodes, which are among the most promising chaotic emitters for secure communications. It is shown that, for edge-emitting lasers, two drastically different synchronization regimes are possible. The regimes differ in terms of the delay time in the synchronization and in terms of the robustness of the synchronization with respect to parameter mismatches between the emitter and the receiver. In vertical-cavity surface-emitting lasers, the two linearly-polarized components of the electric field also exhibit isochronous and anticipating synchronization when the coupling between the lasers is isotropic. When the coupling is polarized, the linearly-polarized component that is parallel to the injected polarization tends to synchronize isochronously with the injected optical field, while the other component tends to be suppressed, but it can also be antisynchronized. The second topic is the analysis of time series produced by optical chaotic emitters subjected to a delayed feedback. First, we verify with experimental data that chaos produced by optical delay systems is highly complex. This high complexity is demonstrated by estimating chaos dimension and entropy from experimental time series and from models of optical delay systems. Second, by analyzing chaotic time series, it is shown that the value of the delay of a single-delay system can always be identified, independently of the type of system used and of its complexity. Unfortunately, an eavesdropper can use this information on the delay value to break the cryptosystem. We propose a new cryptosystem with two delayed feedback loops that increases the difficulty of the delay identification problem.

With the rapid development of optical communications and the increasing amount of data exchanged, it has become utterly important to provide effective ar- chitectures to protect sensitive data. The use of chaotic optoelectronic devices has already demonstrated great potential in terms of additional computational security at the physical layer of the optical network. However, the determination of the security level and the lack of a multi-user framework are two hurdles which have prevented their deployment on a large scale. In this thesis, we propose to address these two issues. First, we investigate the security of a widely used chaotic generator, the external cavity semiconductor laser (ECSL). This is a time-delay system known for providing complex and high-dimensional chaos, but with a low level of security regarding the identification of its most critical parameter, the time delay. We perform a detailed analysis of the influence of the ECSL parameters to devise how higher levels of security can be achieved and provide a physical interpretation of their origin. Second, we devise new architectures to multiplex optical chaotic signals and realize multi-user communications at high bit rates. We propose two different approaches exploiting known chaotic optoelectronic devices. The first one uses mutually cou- pled ECSL and extends typical chaos-based encryption strategies, such as chaos-shift keying (CSK) and chaos modulation (CMo). The second one uses an electro-optical oscillator (EOO) with multiple delayed feedback loops and aims first at transpos- ing coded-division multiple access (CDMA) and then at developing novel strategies of encryption and decryption, when the time-delays of each feedback loop are time- dependent.

The research work presented in this thesis concern to the stability analysis of linear time-delay systems with low-order controllers. This thesis is divided into three parts.The first part of the thesis focus on the study of linear SISO (single-input/single-output) systems with input/output delays, where the feedback loop is closed with a controller of PID-type. Inspired by the geometrical approach developed by Gu et al. we propose an analytical method to find the stability regions of all stabilizing controllers of PID-type for the time-delay system. Based on this same approach, we propose an algorithm to calculate the degree of fragility of a given controller of PID- type (PI, PD and PID).The second part of the thesis focuses on the stability analysis of linear systems under an NCS (Networked System Control) based approach. More precisely, we first focus in the stabilization problem by taking into account the induced network delays and the effects induced by the sampling period. To carry out such an analysis we have adopted an eigenvalue perturbation-based approach.Finally, in the third part of the thesis we tackle certain problems concerning to the behavior of the zeros of a certain class of sampled-data SISO systems. More precisely, given a continuous-time system, we obtain the sampling intervals guaranteeing the invariance of the number of unstable zeros in each interval. To perform such an analysis, we adopt an eigenvalue perturbation-based approach.

Le processus de développement des systèmes avioniques suit des réglementations de sûreté de fonctionnement très strictes, incluant l'analyse du déterminisme et de la prédictibilité temporelle des systèmes. L'approche est basée sur la séparation des étapes de conception et d'implémentation. Une des plus grandes difficultés dans l'approche actuelle se trouve dans la détermination du WCET, qui est nécessaire pour prouver la satisfaction des contraintes de temps-réel dur du système. Dans cette thèse, une méthodologie de relâchement de contraintes temps-réels pour les systèmes de commandes digital est proposé. L'objectif est de réduire le conservatisme des approches traditionnelles basés sur le pire temps d'exécution, tout en préservant la stabilité et les performances de commandes. L'approche a été appliqué au système de commande de tangage d'un avion, ce qui a permi de montrer que le relâchement des contraintes temps réels améliore l'utilisation de la puissance de calcul disponible tout en préservant la stabilité et la qualité de commande du système. / The development process of critical avionics products are done under strict safety regulations. These regulations include determinism and predictability of the systems' timing. The overall approach is based on a separation of concerns between control design and implementation. One of the toughest challenges in the current approach is the determination of the WCET, in order to correctly size the system. In this thesis, a weakened implementation scheme for real-time feedback controllers is proposed to reduce the conservatism due to traditional worst-case considerations, while preserving the stability and control performance. The methodology is tested to the pitch control of an aircraft, showing that weakening the real-time constraints allows for saving computing power while preserving the system's stability and quality of control.

Cette thèse étudie la compensation robuste d'un retard de commande affectant un système dynamique. Pour répondre aux besoins du domaine applicatif du contrôle moteur, nous étudions d'un point de vue théorique des lois de contrôle par prédiction, dans les cas de retards incertains et de retards variables, et présentons des résultats de convergence asymptotique. Dans une première partie, nous proposons une méthodologie générale d'adaptation du retard, à même de traiter également d'autres incertitudes par une analyse de Lyapunov-Krasovskii. Cette analyse est obtenue grâce à une technique d'ajout de dérivateur récemment proposée dans la littérature et exploitant une modélisation du retard sous forme d'une équation à paramètres distribués. Dans une seconde partie, nous établissons des conditions sur les variations admissibles du retard assurant la stabilité du système boucle fermée. Nous nous intéressons tout particulièrement à une famille de retards dépendant de la commande (retard de transport). Des résultats de stabilité inspirés de l'ingalité Halanay sont utilisés pour formuler une condition de petit gain permettant une compensation robuste. Des exemples illustratifs ainsi que des résultats expérimentaux au banc moteur soulignent la compatibilité de ces lois de contrôle avec les impératifs du temps réel ainsi que les mérites de cette approche. / This thesis addresses the general problem of robust compensation of input delays. Motivated by engine applications, we theoretically study prediction-based control laws for uncertain delays and time-varying delays. Results of asymptotic convergence are obtained. In a first part, a general delay-adaptive scheme is proposed to handle uncertainties, through a Lyapunov-Krasovskii analysis induced by a backstepping transformation (applied to a transport equation) recently introduced in the literature.In a second part, conditions to handle delay variability are established. A particular class of input-dependent delay is considered (transport). Halanay-like stability results serve to formulate a small-gain condition guaranteeing robust compensation. Illustrative examples and experimental results obtained on a test bench assess the implementability of the proposed control laws and highlight the merits of the approach.

Dans le domaine de l’ingénierie (par exemple l’aéronautique, l’automobile, la biologie, les circuits), les systèmes dynamiques sont le cadre de base utilisé pour modéliser, contrôler et analyser une grande variété de systèmes et de phénomènes. En raison de l’utilisation croissante de logiciels dédiés de modélisation par ordinateur, la simulation numérique devient de plus en plus utilisée pour simuler un système ou un phénomène complexe et raccourcir le temps de développement et le coût. Cependant, le besoin d’une précision de modèle améliorée conduit inévitablement à un nombre croissant de variables et de ressources à gérer au prix d’un coût numérique élevé. Cette contrepartie justifie la réduction du modèle. Pour les systèmes linéaires invariant dans le temps, plusieurs approches de réduction de modèle ont été effectivement développées depuis les années 60. Parmi celles-ci, les méthodes basées sur l’interpolation se distinguent par leur souplesse et leur faible coût de calcul, ce qui en fait un candidat prédestiné à la réduction de systèmes véritablement à grande échelle. Les progrès récents démontrent des façons de trouver des paramètres de réduction qui minimisent localement la norme H2 de l’erreur d’incompatibilité. En général, une approximation d’ordre réduit est considérée comme un modèle de dimension finie. Cette représentation est assez générale et une large gamme de systèmes dynamiques linéaires peut être convertie sous cette forme, du moins en principe. Cependant, dans certains cas, il peut être plus pertinent de trouver des modèles à ordre réduit ayant des structures plus complexes. A titre d’exemple, certains systèmes de phénomènes de transport ont leurs valeurs singulières Hankel qui se décomposent très lentement et ne sont pas facilement approchées par un modèle de dimension finie. En outre, pour certaines applications, il est intéressant de disposer d’un modèle structuré d’ordre réduit qui reproduit les comportements physiques. C’est pourquoi, dans cette thèse, les modèles à ordre réduit ayant des structures de retard ont été plus précisément considérés. Ce travail a consisté, d’une part, à développer de nouvelles techniques de réduction de modèle pour des modèles à ordre réduit avec des structures de retard et, d’autre part, à trouver de nouvelles applications d’approximation de modèle. La contribution majeure de cette thèse couvre les sujets d’approximation et inclut plusieurs contributions au domaine de la réduction de modèle. Une attention particulière a été accordée au problème de l’approximation du modèle optimale pour les modèles structurés retardés. À cette fin, de nouveaux résultats théoriques et méthodologiques ont été obtenus et appliqués avec succès aux repères académiques et industriels. De plus, la dernière partie de ce manuscrit est consacrée à l’analyse de la stabilité des systèmes retardés par des méthodes interpolatoires. Certaines déclarations théoriques ainsi qu’une heuristique sont développées permettant d’estimer de manière rapide et précise les diagrammes de stabilité de ces systèmes. / In the engineering area (e.g. aerospace, automotive, biology, circuits), dynamical systems are the basic framework used for modeling, controlling and analyzing a large variety of systems and phenomena. Due to the increasing use of dedicated computer-based modeling design software, numerical simulation turns to be more and more used to simulate a complex system or phenomenon and shorten both development time and cost. However, the need of an enhanced model accuracy inevitably leads to an increasing number of variables and resources to manage at the price of a high numerical cost. This counterpart is the justification for model reduction. For linear time-invariant systems, several model reduction approaches have been effectively developed since the 60’s. Among these, interpolation-based methods stand out due to their flexibility and low computational cost, making them a predestined candidate in the reduction of truly large-scale systems. Recent advances demonstrate ways to find reduction parameters that locally minimize the H2 norm of the mismatch error. In general, a reduced-order approximation is considered to be a finite dimensional model. This representation is quite general and a wide range of linear dynamical systems can be converted in this form, at least in principle. However, in some cases, it may be more relevant to find reduced-order models having some more complex structures. As an example, some transport phenomena systems have their Hankel singular values which decay very slowly and are not easily approximated by a finite dimensional model. In addition, for some applications, it is valuable to have a structured reduced-order model which reproduces the physical behaviors. That is why, in this thesis, reduced-order models having delay structures have been more specifically considered. This work has focused, on the one hand, in developing new model reduction techniques for reduced order models having delay structures, and, on the other hand, in finding new applications of model approximation. The major contribution of this thesis covers approximation topics and includes several contributions to the area of model reduction. A special attention was given to the H2 optimal model approximation problem for delayed structured models. For this purpose, some new theoretical and methodological results were derived and successfully applied to both academic and industrial benchmarks. In addition, the last part of this manuscript is dedicated to the analysis of time-delayed systems stability using interpolatory methods. Some theoretical statements as well as an heuristic are developed enabling to estimate in a fast and accurate way the stability charts of those systems.

Cette thèse porte sur la modélisation et l’analyse de stabilité de certains mécanismes biologiques complexes en rapport avec le cancer. Un intérêt particulier est porté au cas de l’hématopoïèse et de la leucémie aiguë myéloblastique (LAM). Les modèles utilisés et/ou introduits dans cette thèse se décrivent par des équations aux dérivées partielles structurées en âge, qui se réduisent à des systèmes à retards de plusieurs types (retards ponctuels ou distribués, à support fini ou infini). Ces modèles à retards sont parfois couplés à des équations aux différences, et possiblement avec des paramètres variant dans le temps. Un des principaux challenges dans ce travail consiste à développer des méthodes temporelles, qui se basent sur la construction de fonctionnelles de Lyapunov-Krasovskii strictes, pour les systèmes non-linéaires à retards étudiés. Les principales notions abordées dans ces travaux incluent : l’analyse de stabilité/stabilisation et de robustesse, l’emploi de techniques de modélisation des populations cellulaires saines et malades, l’étude de différentes classes de systèmes dynamiques, (possiblement à temps variant ou à commutation), et également l’introduction de quelques outils issus de l’intelligence artificielle (planification et recherche de solution) dans un contexte de modèles biologiques. Ainsi, les méthodes de modélisation et d’analyse employées dans ce travail ont permis d’une part d’étendre les résultats de stabilité de cette classe de systèmes biologiques, et d’autre part de mieux comprendre certains mécanismes biologiques liés au cancer et sa thérapie. Plus précisément, certains concepts récemment établis en biologie et en médecine sont mis en évidence dans ce travail pour la première fois dans cette classe de systèmes, telles que : la dédifférenciation des cellules (plasticité), ou encore la dormance des cellules cancéreuses dans des modèles tenant compte de la cohabitation entre cellules saines et mutées. Les résultats obtenus sont interprétés dans le cas de l’hématopoïèse et de la LAM, mais ce travail s’applique également à d’autres types de tissus où le cycle cellulaire se produit de façon similaire. / Medical research is looking for new combined targeted therapies against cancer. Our research project -which involves intensive collaboration with hematologists from Saint-Antoine Hospital in Paris- is imbued within a similar spirit and fits the expectations of a better understanding of the behavior of blood cell dynamics. In fact, hematopoiesis provides a paradigm for studying all the mammalian stem cells, as well as all the mechanisms involved in the cell cycle. We address multiple issues related to the modeling and analysis of the cell cycle, with particular insights into the hematopoietic systems. Stability features of the models are highlighted, since systems trajectories reflect the most prominent healthy or unhealthy behaviors of the biological process under study. We indeed perform stability analysis of systems describing healthy and unhealthy situations, with a particular interest in the case of acute myeloblastic leukemia (AML). Thus, we pursue the objectives of understanding the interactions between the various parameters and functions involved in the mechanisms of interest. For that purpose, an advanced stability analysis of the cell fate evolution in treated or untreated leukemia is performed in several modeling frameworks, and our study suggests new anti-leukemic combined chemotherapy. Throughout the thesis, we cover many biological evidences that are currently undergoing intensive biological research, such as: cell plasticity, mutations accumulation, cohabitation between ordinary and mutated cells, control or eradication of cancer cells, cancer dormancy, etc.Among the contributions of Part I of the thesis, we can mention the extension of both modeling and analysis aspects in order to take into account a proliferating phase in which most of the cells may divide, or die, while few of them may be arrested during their cycle for unlimited time. We also introduce for the first time cell-plasticity features to the class of systems that we are focusing on.Next, in Part II, stability analyses of some differential-difference cell population models are performed through several time-domain techniques, including tools of Comparative and Positive Systems approaches. Then, a new age-structured model describing the coexistence between cancer and ordinary stem cells is introduced. This model is transformed into a nonlinear time-delay system that describes the dynamics of healthy cells, coupled to a nonlinear differential-difference system governing the dynamics of unhealthy cells. The main features of the coupled system are highlighted and an advanced stability analysis of several coexisting steady states is performed through a Lyapunov-like approach for descriptor-type systems. We pursue an analysis that provides a theoretical treatment framework following different medical orientations, among which: i) the case where therapy aims to eradicate cancer cells while preserving healthy ones, and ii) a less demanding, more realistic, scenario that consists in maintaining healthy and unhealthy cells in a controlled stable dormancy steady-state. Mainly, sufficient conditions for the regional exponential stability, estimate of the decay rate of the solutions, and subsets of the basins of attraction of the steady states of interest are provided. Biological interpretations and therapeutic strategies in light of emerging AML-drugs are discussed according to our findings.Finally, in Part III, an original formulation of what can be interpreted as a stabilization issue of population cell dynamics through artificial intelligence planning tools is provided. In that framework, an optimal solution is discovered via planning and scheduling algorithms. For unhealthy hematopoiesis, we address the treatment issue through multiple drug infusions. In that case, we determine the best therapeutic strategy that restores normal blood count as in an ordinary hematopoietic system.